Numero
Statistical Framework to Define Subgroups in Complex Datasets
Song Gao, Stefan Mutter, Ville-Petteri Makinen, Aaron E. Casey
Last update: 6 February 2024
Copyright license: GNU General Public License, version 3.0, GNU General Public License, version 2.0
Software version identifier: 1.9.5, 1.0.3, 1.1.1, 1.2.0, 1.3.1, 1.3.2, 1.3.3, 1.4.0, 1.4.1, 1.4.2, 1.5.0, 1.6.0, 1.7.0, 1.7.2, 1.7.3, 1.7.4, 1.8.0, 1.8.1, 1.8.2, 1.8.4, 1.9.0, 1.9.3, 1.9.6
High-dimensional datasets that do not exhibit a clear intrinsic clustered structure pose a challenge to conventional clustering algorithms. For this reason, we developed an unsupervised framework that helps scientists to better subgroup their datasets based on visual cues, please see Gao S, Mutter S, Casey A, Makinen V-P (2019) Numero: a statistical framework to define multivariable subgroups in complex population-based datasets, Int J Epidemiology, 48:369-37, <doi:10.1093/ije/dyy113>. The framework includes the necessary functions to construct a self-organizing map of the data, to evaluate the statistical significance of the observed data patterns, and to visualize the results.
This page was built for software: Numero
